Publications related to Modeling Individual and Group Actions in Meetings: a Two-Layer HMM Framework

Intraday solar irradiance forecasting using public cameras

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With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

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Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

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Modeling Individual and Group Actions in Meetings: a Two-Layer HMM Framework

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Intraday solar irradiance forecasting using public cameras

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Random matrix methods for high-dimensional machine learning models

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Intraday solar irradiance forecasting using public cameras

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Random matrix methods for high-dimensional machine learning models

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs